Non-cooperative inference method for physical topology of Ad Hoc network

Abstract

The invention relates to a non-cooperative inference method for the physical topology of an Ad Hoc network, and belongs to the technical field of wireless networks. The method comprises the steps of S1, differentiating and positioning nodes in the Ad Hoc network by adopting radio positioning; S2, obtaining the size of a network deployment area according to the node differentiating and positioninginformation; S3, calculating the important communication distance of the nodes according to the size of the network deployment area and the node differentiating and positioning information; and S4, inferring the physical topology of the network according to the node differentiating and positioning information and the important communication distance of the nodes. The method realizes automatic inference of the network physical topology without knowing the relevant parameters such as the node communication power. Compared with the existing methods, the method improves the structural validity ofthe network physical topology and reduces the calculation complexity of the implementation process.

Description

technical field [0001] The present invention relates to the technical field of wireless networks, in particular to a construction method for Ad Hoc network physical topology non-cooperative inference and optimization. Background technique [0002] Ad Hoc networks can be quickly deployed and do not need to set up network facilities, making them widely used in both civilian and military applications. [0003] Existing research on network topology mainly focuses on logical topology. In the process of physical topology analysis, it is mainly based on the known maximum communication distance of nodes or using the longest distance of the minimum spanning tree constructed by network nodes as the maximum communication distance. Since it is usually deployed in an unsafe area, it is difficult to obtain the maximum communication distance of the node without knowing the relevant parameters such as the communication power of the node. Using the longest distance of the minimum spanning t...

AI Technical Summary

Problems solved by technology

Since it is usually deployed in an unsafe area, it is difficult to obtain the maximum communication distance of a node in the case of unknown node communication power and other related parameters

Using the longest distance of the minimum spanning tree as the maximum communication distance does not take into account the situation that a single node is out of the network and cannot effectively deal with changes in node positions. Every time a node changes its position, the minimum spanning tree must be rebuilt to calculate the longest distance, resulting in increase in computational complexity

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